{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "from keras.models import load_model\n",
    "import keras.backend as K\n",
    "from os.path import join\n",
    "from scipy.ndimage import gaussian_filter\n",
    "from glob import glob\n",
    "import pickle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['/scratch/dgagne/spatial_storm_results_20171220/logistic_gan_0_encoder.h5',\n",
       " '/scratch/dgagne/spatial_storm_results_20171220/logistic_gan_10_encoder.h5',\n",
       " '/scratch/dgagne/spatial_storm_results_20171220/logistic_gan_11_encoder.h5',\n",
       " '/scratch/dgagne/spatial_storm_results_20171220/logistic_gan_12_encoder.h5',\n",
       " '/scratch/dgagne/spatial_storm_results_20171220/logistic_gan_13_encoder.h5',\n",
       " '/scratch/dgagne/spatial_storm_results_20171220/logistic_gan_14_encoder.h5',\n",
       " '/scratch/dgagne/spatial_storm_results_20171220/logistic_gan_15_encoder.h5',\n",
       " '/scratch/dgagne/spatial_storm_results_20171220/logistic_gan_16_encoder.h5',\n",
       " '/scratch/dgagne/spatial_storm_results_20171220/logistic_gan_17_encoder.h5',\n",
       " '/scratch/dgagne/spatial_storm_results_20171220/logistic_gan_18_encoder.h5',\n",
       " '/scratch/dgagne/spatial_storm_results_20171220/logistic_gan_19_encoder.h5',\n",
       " '/scratch/dgagne/spatial_storm_results_20171220/logistic_gan_1_encoder.h5',\n",
       " '/scratch/dgagne/spatial_storm_results_20171220/logistic_gan_20_encoder.h5',\n",
       " '/scratch/dgagne/spatial_storm_results_20171220/logistic_gan_21_encoder.h5',\n",
       " '/scratch/dgagne/spatial_storm_results_20171220/logistic_gan_22_encoder.h5',\n",
       " '/scratch/dgagne/spatial_storm_results_20171220/logistic_gan_23_encoder.h5',\n",
       " '/scratch/dgagne/spatial_storm_results_20171220/logistic_gan_24_encoder.h5',\n",
       " '/scratch/dgagne/spatial_storm_results_20171220/logistic_gan_25_encoder.h5',\n",
       " '/scratch/dgagne/spatial_storm_results_20171220/logistic_gan_26_encoder.h5',\n",
       " '/scratch/dgagne/spatial_storm_results_20171220/logistic_gan_27_encoder.h5',\n",
       " '/scratch/dgagne/spatial_storm_results_20171220/logistic_gan_28_encoder.h5',\n",
       " '/scratch/dgagne/spatial_storm_results_20171220/logistic_gan_29_encoder.h5',\n",
       " '/scratch/dgagne/spatial_storm_results_20171220/logistic_gan_2_encoder.h5',\n",
       " '/scratch/dgagne/spatial_storm_results_20171220/logistic_gan_3_encoder.h5',\n",
       " '/scratch/dgagne/spatial_storm_results_20171220/logistic_gan_4_encoder.h5',\n",
       " '/scratch/dgagne/spatial_storm_results_20171220/logistic_gan_5_encoder.h5',\n",
       " '/scratch/dgagne/spatial_storm_results_20171220/logistic_gan_6_encoder.h5',\n",
       " '/scratch/dgagne/spatial_storm_results_20171220/logistic_gan_7_encoder.h5',\n",
       " '/scratch/dgagne/spatial_storm_results_20171220/logistic_gan_8_encoder.h5',\n",
       " '/scratch/dgagne/spatial_storm_results_20171220/logistic_gan_9_encoder.h5']"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "path = \"/scratch/dgagne/spatial_storm_results_20171220/\"\n",
    "sorted(glob(join(path, \"logistic_gan_*_encoder.h5\")))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "gan_enc = load_model('/scratch/dgagne/spatial_storm_results_20171220/logistic_gan_0_encoder.h5')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/scratch/dgagne/miniconda3/envs/deep36/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88\n",
      "  return f(*args, **kwds)\n",
      "/scratch/dgagne/miniconda3/envs/deep36/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88\n",
      "  return f(*args, **kwds)\n"
     ]
    }
   ],
   "source": [
    "gan_log_filename = \"/scratch/dgagne/spatial_storm_results_20171220/logistic_gan_0_logistic.pkl\"\n",
    "with open(gan_log_filename, \"rb\") as gan_log_file:\n",
    "    gan_log = pickle.load(gan_log_file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3.37472\n",
      "2.22954\n",
      "1.34371\n",
      "0.702153\n",
      "0.293162\n",
      "0.0697176\n",
      "7.71906e-06\n",
      "0.0608188\n",
      "4.9028e-06\n",
      "0.0605409\n",
      "2.93154e-06\n",
      "0.0602774\n",
      "1.52707e-06\n",
      "0.0600303\n",
      "6.09273e-07\n",
      "0.0598085\n",
      "1.17585e-07\n",
      "0.0595614\n",
      "1.31422e-08\n",
      "0.0668271\n",
      "2.75428e-07\n",
      "0.0589734\n",
      "2.50067e-08\n",
      "0.0587864\n",
      "3.24185e-08\n",
      "0.0659067\n",
      "2.40017e-07\n",
      "0.058264\n",
      "6.95222e-08\n",
      "0.0581339\n",
      "2.32478e-09\n",
      "0.0580152\n",
      "2.44236e-08\n",
      "0.0650088\n",
      "2.57675e-07\n",
      "0.0575403\n",
      "9.39373e-08\n",
      "0.0574339\n",
      "1.56058e-08\n",
      "0.0573315\n",
      "1.86265e-09\n",
      "0.0641994\n",
      "3.81558e-07\n",
      "0.0568995\n",
      "1.81063e-07\n",
      "0.0568055\n",
      "6.58384e-08\n",
      "0.056712\n",
      "9.29913e-09\n",
      "0.0566285\n"
     ]
    }
   ],
   "source": [
    "out = gan_enc.layers[-1].output[0, 2]\n",
    "input_image = gan_enc.input\n",
    "loss = 0.5 * (out - 3) ** 2\n",
    "grads = K.gradients(loss, input_image)[0]\n",
    "grads /= K.maximum(K.std(grads), K.epsilon())\n",
    "iterate = K.function([input_image, K.learning_phase()], \n",
    "                     [loss, grads])\n",
    "input_ex = np.zeros((1, 32 ,32 , 15))\n",
    "for i in range(50):\n",
    "    loss_val, grad_val = iterate([input_ex, 0])\n",
    "    input_ex -= 0.01 * grad_val\n",
    "    print(loss_val)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x7f9c29038a58>"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9cd00b6748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.pcolormesh(gaussian_filter(input_ex[0, :, :, 14], 1))\n",
    "plt.colorbar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.quiver.Quiver at 0x7f9c291f5a90>"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9cd009e860>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.quiver(gaussian_filter(input_ex[0, :, :, 11], 1), gaussian_filter(input_ex[0, :, :, 14], 1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gan_log.coef_.argmax()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
